Rotation-Invariant and Relation-Aware Cross-Domain Adaptation Object Detection Network for Optical Remote Sensing Images
In recent years, object detection has shown excellent results on a large number of annotated data, but when there is a discrepancy between the annotated data and the real test data, the performance of the trained object detection model is often degraded when it is directly transferred to the real te...
Saved in:
Main Authors: | Ying Chen, Qi Liu, Teng Wang, Bin Wang, Xiaoliang Meng |
---|---|
Format: | article |
Language: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/ed656ef591a44896bcc2c5286e5cf6fc |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Constraint Loss for Rotated Object Detection in Remote Sensing Images
by: Luyang Zhang, et al.
Published: (2021) -
Improved Oriented Object Detection in Remote Sensing Images Based on a Three-Point Regression Method
by: Falin Wu, et al.
Published: (2021) -
Attention Mask R-CNN for Ship Detection and Segmentation From Remote Sensing Images
by: Xuan Nie, et al.
Published: (2020) -
Unsupervised Deep Learning for Landslide Detection from Multispectral Sentinel-2 Imagery
by: Hejar Shahabi, et al.
Published: (2021) -
SGA-Net: Self-Constructing Graph Attention Neural Network for Semantic Segmentation of Remote Sensing Images
by: Wenjie Zi, et al.
Published: (2021)